A multi-frequency whole-brain neural mass model with homeostatic feedback inhibition.

Whole-brain models are valuable tools for understanding brain dynamics in health and disease by enabling the testing of causal mechanisms and identification of therapeutic targets through dynamic simulations. Among these models, biophysically inspired neural mass models have been widely used to simulate electrophysiological recordings, such as MEG and EEG. However, traditional models face limitations, including susceptibility to hyperexcitation, which constrains their ability to capture the full richness of neural dynamics.

An integrated computational approach for diversity-sensitive personalized medicine.

Diversity in biological, social, and environmental factors plays a central role in shaping brain health and disease. Distinct brain disorders frequently exhibit overlapping clinical phenotypes, despite arising from heterogeneous biological and contextual mechanisms. This convergence challenges conventional, population-averaged approaches, which often fail to capture interindividual variability and lead to limited reproducibility, weak translational potential, and inadequate tools for individual-level characterization.

Temporal dynamics of offline transcranial ultrasound stimulation.

Transcranial ultrasound stimulation (TUS) is a promising non-invasive neuromodulation modality, characterized by deep-brain accuracy and the capability to induce longer-lasting effects. However, most TUS datasets are underpowered, hampering efforts to identify TUS longevity and temporal dynamics. This primate case was studied awake with over 50 fMRI datasets, with and without left anterior hippocampus TUS.

Delay- and Pressure-Dependent Neuromodulatory Effects of Transcranial Ultrasound Stimulation.

Objective: Despite the growing interest in transcranial focused ultrasound stimulation (TUS), our understanding of its underlying mechanisms remains limited. In this study, we aimed to investigate the effects of TUS on several functional magnetic resonance imaging metrics by considering their latency, duration, and relationship with applied acoustic pressure.

Materials And Methods: We recruited 22 healthy volunteers and used a pre- vs post-TUS protocol.

A Taxonomy of Neuroscientific Strategies Based on Interaction Orders.

In recent decades, neuroscience has advanced with increasingly sophisticated strategies for recording and analysing brain activity, enabling detailed investigations into the roles of functional units, such as individual neurons, brain regions and their interactions. Recently, new strategies for the investigation of cognitive functions regard the study of higher order interactions-that is, the interactions involving more than two brain regions or neurons. Although methods focusing on individual units and their interactions at various levels offer valuable and often complementary insights, each approach comes with its own set of limitations.

Transcranial ultrasound stimulation effect in the redundant and synergistic networks consistent across macaques.

Low-intensity transcranial ultrasound stimulation (TUS) is a noninvasive technique that safely alters neural activity, reaching deep brain areas with good spatial accuracy. We investigated the effects of TUS in macaques using a recent metric, the synergy minus redundancy rank gradient, which quantifies different kinds of neural information processing. We analyzed this high-order quantity on the fMRI data after TUS in two targets: the supplementary motor area (SMA-TUS) and the frontal polar cortex (FPC-TUS).

High-order functional redundancy in ageing explained via alterations in the connectome in a whole-brain model.

The human brain generates a rich repertoire of spatio-temporal activity patterns, which support a wide variety of motor and cognitive functions. These patterns of activity change with age in a multi-factorial manner. One of these factors is the variations in the brain's connectomics that occurs along the lifespan.

High-Order Interdependencies in the Aging Brain.

Brain interdependencies can be studied from either a structural/anatomical perspective ("structural connectivity") or by considering statistical interdependencies ("functional connectivity" [FC]). Interestingly, while structural connectivity is by definition pairwise (white-matter fibers project from one region to another), FC is not. However, most FC analyses only focus on pairwise statistics and they neglect higher order interactions.